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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationThu, 17 Dec 2009 05:52:26 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/17/t1261054459cbn2jp1j17i3v3w.htm/, Retrieved Tue, 30 Apr 2024 00:31:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68833, Retrieved Tue, 30 Apr 2024 00:31:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsSHW Paper: (Partial) Autocorrelation function
Estimated Impact120

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:16:10] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [WS 8 Methode 1: A...] [2009-11-25 13:03:23] [b103a1dc147def8132c7f643ad8c8f84]
-    D            [(Partial) Autocorrelation Function] [Paper: (Partial) ...] [2009-12-17 12:52:26] [a45cc820faa25ce30779915639528ec2] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
15.5
15.1
11.7
16.3
16.7
15
14.9
14.6
15.3
17.9
16.4
15.4
17.9
15.9
13.9
17.8
17.9
17.4
16.7
16
16.6
19.1
17.8
17.2
18.6
16.3
15.1
19.2
17.7
19.1
18
17.5
17.8
21.1
17.2
19.4
19.8
17.6
16.2
19.5
19.9
20
17.3
18.9
18.6
21.4
18.6
19.8
20.8
19.6
17.7
19.8
22.2
20.7
17.9
20.9
21.2
21.4
23
21.3
23.9
22.4
18.3
22.8
22.3
17.8
16.4
16
16.4
17.7
16.6
16.2
18.3

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68833&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68833&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68833&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.6133495.24051e-06
20.4677843.99677.6e-05
30.541734.62858e-06
40.5044584.31012.5e-05
50.4352293.71860.000195
60.422953.61370.000276
70.2541942.17180.016559
80.3108662.6560.004852
90.2171071.8550.03382
100.0852630.72850.234324
110.2095911.79070.03874
120.3869173.30580.000735
130.1540711.31640.096082
140.0636950.54420.293977
150.1052170.8990.185812
160.1457951.24570.108434
170.1069940.91420.181823
180.1145920.97910.165387
190.049140.41990.337913
200.0663970.56730.286128
21-0.014879-0.12710.449594
22-0.078018-0.66660.253568
230.0214940.18360.427402
240.122661.0480.149045
25-0.017222-0.14710.441712
26-0.119799-1.02360.15471
27-0.088926-0.75980.224916
28-0.017617-0.15050.440384
29-0.088646-0.75740.225626
30-0.083108-0.71010.239959
31-0.0978-0.83560.203052
32-0.1305-1.1150.134255
33-0.179228-1.53130.065006
34-0.19608-1.67530.049077
35-0.183053-1.5640.061071
36-0.069485-0.59370.277282

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.613349 & 5.2405 & 1e-06 \tabularnewline
2 & 0.467784 & 3.9967 & 7.6e-05 \tabularnewline
3 & 0.54173 & 4.6285 & 8e-06 \tabularnewline
4 & 0.504458 & 4.3101 & 2.5e-05 \tabularnewline
5 & 0.435229 & 3.7186 & 0.000195 \tabularnewline
6 & 0.42295 & 3.6137 & 0.000276 \tabularnewline
7 & 0.254194 & 2.1718 & 0.016559 \tabularnewline
8 & 0.310866 & 2.656 & 0.004852 \tabularnewline
9 & 0.217107 & 1.855 & 0.03382 \tabularnewline
10 & 0.085263 & 0.7285 & 0.234324 \tabularnewline
11 & 0.209591 & 1.7907 & 0.03874 \tabularnewline
12 & 0.386917 & 3.3058 & 0.000735 \tabularnewline
13 & 0.154071 & 1.3164 & 0.096082 \tabularnewline
14 & 0.063695 & 0.5442 & 0.293977 \tabularnewline
15 & 0.105217 & 0.899 & 0.185812 \tabularnewline
16 & 0.145795 & 1.2457 & 0.108434 \tabularnewline
17 & 0.106994 & 0.9142 & 0.181823 \tabularnewline
18 & 0.114592 & 0.9791 & 0.165387 \tabularnewline
19 & 0.04914 & 0.4199 & 0.337913 \tabularnewline
20 & 0.066397 & 0.5673 & 0.286128 \tabularnewline
21 & -0.014879 & -0.1271 & 0.449594 \tabularnewline
22 & -0.078018 & -0.6666 & 0.253568 \tabularnewline
23 & 0.021494 & 0.1836 & 0.427402 \tabularnewline
24 & 0.12266 & 1.048 & 0.149045 \tabularnewline
25 & -0.017222 & -0.1471 & 0.441712 \tabularnewline
26 & -0.119799 & -1.0236 & 0.15471 \tabularnewline
27 & -0.088926 & -0.7598 & 0.224916 \tabularnewline
28 & -0.017617 & -0.1505 & 0.440384 \tabularnewline
29 & -0.088646 & -0.7574 & 0.225626 \tabularnewline
30 & -0.083108 & -0.7101 & 0.239959 \tabularnewline
31 & -0.0978 & -0.8356 & 0.203052 \tabularnewline
32 & -0.1305 & -1.115 & 0.134255 \tabularnewline
33 & -0.179228 & -1.5313 & 0.065006 \tabularnewline
34 & -0.19608 & -1.6753 & 0.049077 \tabularnewline
35 & -0.183053 & -1.564 & 0.061071 \tabularnewline
36 & -0.069485 & -0.5937 & 0.277282 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68833&T=1

[TABLE]
[ROW][C]Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]ACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.613349[/C][C]5.2405[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]0.467784[/C][C]3.9967[/C][C]7.6e-05[/C][/ROW]
[ROW][C]3[/C][C]0.54173[/C][C]4.6285[/C][C]8e-06[/C][/ROW]
[ROW][C]4[/C][C]0.504458[/C][C]4.3101[/C][C]2.5e-05[/C][/ROW]
[ROW][C]5[/C][C]0.435229[/C][C]3.7186[/C][C]0.000195[/C][/ROW]
[ROW][C]6[/C][C]0.42295[/C][C]3.6137[/C][C]0.000276[/C][/ROW]
[ROW][C]7[/C][C]0.254194[/C][C]2.1718[/C][C]0.016559[/C][/ROW]
[ROW][C]8[/C][C]0.310866[/C][C]2.656[/C][C]0.004852[/C][/ROW]
[ROW][C]9[/C][C]0.217107[/C][C]1.855[/C][C]0.03382[/C][/ROW]
[ROW][C]10[/C][C]0.085263[/C][C]0.7285[/C][C]0.234324[/C][/ROW]
[ROW][C]11[/C][C]0.209591[/C][C]1.7907[/C][C]0.03874[/C][/ROW]
[ROW][C]12[/C][C]0.386917[/C][C]3.3058[/C][C]0.000735[/C][/ROW]
[ROW][C]13[/C][C]0.154071[/C][C]1.3164[/C][C]0.096082[/C][/ROW]
[ROW][C]14[/C][C]0.063695[/C][C]0.5442[/C][C]0.293977[/C][/ROW]
[ROW][C]15[/C][C]0.105217[/C][C]0.899[/C][C]0.185812[/C][/ROW]
[ROW][C]16[/C][C]0.145795[/C][C]1.2457[/C][C]0.108434[/C][/ROW]
[ROW][C]17[/C][C]0.106994[/C][C]0.9142[/C][C]0.181823[/C][/ROW]
[ROW][C]18[/C][C]0.114592[/C][C]0.9791[/C][C]0.165387[/C][/ROW]
[ROW][C]19[/C][C]0.04914[/C][C]0.4199[/C][C]0.337913[/C][/ROW]
[ROW][C]20[/C][C]0.066397[/C][C]0.5673[/C][C]0.286128[/C][/ROW]
[ROW][C]21[/C][C]-0.014879[/C][C]-0.1271[/C][C]0.449594[/C][/ROW]
[ROW][C]22[/C][C]-0.078018[/C][C]-0.6666[/C][C]0.253568[/C][/ROW]
[ROW][C]23[/C][C]0.021494[/C][C]0.1836[/C][C]0.427402[/C][/ROW]
[ROW][C]24[/C][C]0.12266[/C][C]1.048[/C][C]0.149045[/C][/ROW]
[ROW][C]25[/C][C]-0.017222[/C][C]-0.1471[/C][C]0.441712[/C][/ROW]
[ROW][C]26[/C][C]-0.119799[/C][C]-1.0236[/C][C]0.15471[/C][/ROW]
[ROW][C]27[/C][C]-0.088926[/C][C]-0.7598[/C][C]0.224916[/C][/ROW]
[ROW][C]28[/C][C]-0.017617[/C][C]-0.1505[/C][C]0.440384[/C][/ROW]
[ROW][C]29[/C][C]-0.088646[/C][C]-0.7574[/C][C]0.225626[/C][/ROW]
[ROW][C]30[/C][C]-0.083108[/C][C]-0.7101[/C][C]0.239959[/C][/ROW]
[ROW][C]31[/C][C]-0.0978[/C][C]-0.8356[/C][C]0.203052[/C][/ROW]
[ROW][C]32[/C][C]-0.1305[/C][C]-1.115[/C][C]0.134255[/C][/ROW]
[ROW][C]33[/C][C]-0.179228[/C][C]-1.5313[/C][C]0.065006[/C][/ROW]
[ROW][C]34[/C][C]-0.19608[/C][C]-1.6753[/C][C]0.049077[/C][/ROW]
[ROW][C]35[/C][C]-0.183053[/C][C]-1.564[/C][C]0.061071[/C][/ROW]
[ROW][C]36[/C][C]-0.069485[/C][C]-0.5937[/C][C]0.277282[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68833&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68833&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.6133495.24051e-06
20.4677843.99677.6e-05
30.541734.62858e-06
40.5044584.31012.5e-05
50.4352293.71860.000195
60.422953.61370.000276
70.2541942.17180.016559
80.3108662.6560.004852
90.2171071.8550.03382
100.0852630.72850.234324
110.2095911.79070.03874
120.3869173.30580.000735
130.1540711.31640.096082
140.0636950.54420.293977
150.1052170.8990.185812
160.1457951.24570.108434
170.1069940.91420.181823
180.1145920.97910.165387
190.049140.41990.337913
200.0663970.56730.286128
21-0.014879-0.12710.449594
22-0.078018-0.66660.253568
230.0214940.18360.427402
240.122661.0480.149045
25-0.017222-0.14710.441712
26-0.119799-1.02360.15471
27-0.088926-0.75980.224916
28-0.017617-0.15050.440384
29-0.088646-0.75740.225626
30-0.083108-0.71010.239959
31-0.0978-0.83560.203052
32-0.1305-1.1150.134255
33-0.179228-1.53130.065006
34-0.19608-1.67530.049077
35-0.183053-1.5640.061071
36-0.069485-0.59370.277282






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.6133495.24051e-06
20.1468211.25440.106843
30.3389632.89610.002491
40.1005580.85920.196531
50.0569850.48690.313902
60.0515330.44030.33051
7-0.258116-2.20530.01529
80.160361.37010.087426
9-0.246861-2.10920.01918
10-0.079032-0.67530.250824
110.2447742.09130.019988
120.3946093.37150.000599
13-0.196349-1.67760.048851
14-0.210748-1.80060.037946
15-0.066905-0.57160.284663
160.0091450.07810.468969
17-0.115706-0.98860.163065
180.1478731.26340.105228
190.1270541.08560.140625
20-0.097304-0.83140.20424
21-0.094635-0.80860.210697
220.0072970.06230.475229
230.024280.20750.418117
24-0.085514-0.73060.233672
250.0854190.72980.233918
26-0.067834-0.57960.281993
27-0.078779-0.67310.251509
280.0399920.34170.366781
29-0.100707-0.86040.196182
30-0.004622-0.03950.484305
31-0.030444-0.26010.397755
320.004440.03790.48492
33-0.001603-0.01370.494556
340.0034210.02920.48838
35-0.10958-0.93630.176115
360.0030030.02570.4898

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.613349 & 5.2405 & 1e-06 \tabularnewline
2 & 0.146821 & 1.2544 & 0.106843 \tabularnewline
3 & 0.338963 & 2.8961 & 0.002491 \tabularnewline
4 & 0.100558 & 0.8592 & 0.196531 \tabularnewline
5 & 0.056985 & 0.4869 & 0.313902 \tabularnewline
6 & 0.051533 & 0.4403 & 0.33051 \tabularnewline
7 & -0.258116 & -2.2053 & 0.01529 \tabularnewline
8 & 0.16036 & 1.3701 & 0.087426 \tabularnewline
9 & -0.246861 & -2.1092 & 0.01918 \tabularnewline
10 & -0.079032 & -0.6753 & 0.250824 \tabularnewline
11 & 0.244774 & 2.0913 & 0.019988 \tabularnewline
12 & 0.394609 & 3.3715 & 0.000599 \tabularnewline
13 & -0.196349 & -1.6776 & 0.048851 \tabularnewline
14 & -0.210748 & -1.8006 & 0.037946 \tabularnewline
15 & -0.066905 & -0.5716 & 0.284663 \tabularnewline
16 & 0.009145 & 0.0781 & 0.468969 \tabularnewline
17 & -0.115706 & -0.9886 & 0.163065 \tabularnewline
18 & 0.147873 & 1.2634 & 0.105228 \tabularnewline
19 & 0.127054 & 1.0856 & 0.140625 \tabularnewline
20 & -0.097304 & -0.8314 & 0.20424 \tabularnewline
21 & -0.094635 & -0.8086 & 0.210697 \tabularnewline
22 & 0.007297 & 0.0623 & 0.475229 \tabularnewline
23 & 0.02428 & 0.2075 & 0.418117 \tabularnewline
24 & -0.085514 & -0.7306 & 0.233672 \tabularnewline
25 & 0.085419 & 0.7298 & 0.233918 \tabularnewline
26 & -0.067834 & -0.5796 & 0.281993 \tabularnewline
27 & -0.078779 & -0.6731 & 0.251509 \tabularnewline
28 & 0.039992 & 0.3417 & 0.366781 \tabularnewline
29 & -0.100707 & -0.8604 & 0.196182 \tabularnewline
30 & -0.004622 & -0.0395 & 0.484305 \tabularnewline
31 & -0.030444 & -0.2601 & 0.397755 \tabularnewline
32 & 0.00444 & 0.0379 & 0.48492 \tabularnewline
33 & -0.001603 & -0.0137 & 0.494556 \tabularnewline
34 & 0.003421 & 0.0292 & 0.48838 \tabularnewline
35 & -0.10958 & -0.9363 & 0.176115 \tabularnewline
36 & 0.003003 & 0.0257 & 0.4898 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68833&T=2

[TABLE]
[ROW][C]Partial Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]PACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.613349[/C][C]5.2405[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]0.146821[/C][C]1.2544[/C][C]0.106843[/C][/ROW]
[ROW][C]3[/C][C]0.338963[/C][C]2.8961[/C][C]0.002491[/C][/ROW]
[ROW][C]4[/C][C]0.100558[/C][C]0.8592[/C][C]0.196531[/C][/ROW]
[ROW][C]5[/C][C]0.056985[/C][C]0.4869[/C][C]0.313902[/C][/ROW]
[ROW][C]6[/C][C]0.051533[/C][C]0.4403[/C][C]0.33051[/C][/ROW]
[ROW][C]7[/C][C]-0.258116[/C][C]-2.2053[/C][C]0.01529[/C][/ROW]
[ROW][C]8[/C][C]0.16036[/C][C]1.3701[/C][C]0.087426[/C][/ROW]
[ROW][C]9[/C][C]-0.246861[/C][C]-2.1092[/C][C]0.01918[/C][/ROW]
[ROW][C]10[/C][C]-0.079032[/C][C]-0.6753[/C][C]0.250824[/C][/ROW]
[ROW][C]11[/C][C]0.244774[/C][C]2.0913[/C][C]0.019988[/C][/ROW]
[ROW][C]12[/C][C]0.394609[/C][C]3.3715[/C][C]0.000599[/C][/ROW]
[ROW][C]13[/C][C]-0.196349[/C][C]-1.6776[/C][C]0.048851[/C][/ROW]
[ROW][C]14[/C][C]-0.210748[/C][C]-1.8006[/C][C]0.037946[/C][/ROW]
[ROW][C]15[/C][C]-0.066905[/C][C]-0.5716[/C][C]0.284663[/C][/ROW]
[ROW][C]16[/C][C]0.009145[/C][C]0.0781[/C][C]0.468969[/C][/ROW]
[ROW][C]17[/C][C]-0.115706[/C][C]-0.9886[/C][C]0.163065[/C][/ROW]
[ROW][C]18[/C][C]0.147873[/C][C]1.2634[/C][C]0.105228[/C][/ROW]
[ROW][C]19[/C][C]0.127054[/C][C]1.0856[/C][C]0.140625[/C][/ROW]
[ROW][C]20[/C][C]-0.097304[/C][C]-0.8314[/C][C]0.20424[/C][/ROW]
[ROW][C]21[/C][C]-0.094635[/C][C]-0.8086[/C][C]0.210697[/C][/ROW]
[ROW][C]22[/C][C]0.007297[/C][C]0.0623[/C][C]0.475229[/C][/ROW]
[ROW][C]23[/C][C]0.02428[/C][C]0.2075[/C][C]0.418117[/C][/ROW]
[ROW][C]24[/C][C]-0.085514[/C][C]-0.7306[/C][C]0.233672[/C][/ROW]
[ROW][C]25[/C][C]0.085419[/C][C]0.7298[/C][C]0.233918[/C][/ROW]
[ROW][C]26[/C][C]-0.067834[/C][C]-0.5796[/C][C]0.281993[/C][/ROW]
[ROW][C]27[/C][C]-0.078779[/C][C]-0.6731[/C][C]0.251509[/C][/ROW]
[ROW][C]28[/C][C]0.039992[/C][C]0.3417[/C][C]0.366781[/C][/ROW]
[ROW][C]29[/C][C]-0.100707[/C][C]-0.8604[/C][C]0.196182[/C][/ROW]
[ROW][C]30[/C][C]-0.004622[/C][C]-0.0395[/C][C]0.484305[/C][/ROW]
[ROW][C]31[/C][C]-0.030444[/C][C]-0.2601[/C][C]0.397755[/C][/ROW]
[ROW][C]32[/C][C]0.00444[/C][C]0.0379[/C][C]0.48492[/C][/ROW]
[ROW][C]33[/C][C]-0.001603[/C][C]-0.0137[/C][C]0.494556[/C][/ROW]
[ROW][C]34[/C][C]0.003421[/C][C]0.0292[/C][C]0.48838[/C][/ROW]
[ROW][C]35[/C][C]-0.10958[/C][C]-0.9363[/C][C]0.176115[/C][/ROW]
[ROW][C]36[/C][C]0.003003[/C][C]0.0257[/C][C]0.4898[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68833&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68833&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.6133495.24051e-06
20.1468211.25440.106843
30.3389632.89610.002491
40.1005580.85920.196531
50.0569850.48690.313902
60.0515330.44030.33051
7-0.258116-2.20530.01529
80.160361.37010.087426
9-0.246861-2.10920.01918
10-0.079032-0.67530.250824
110.2447742.09130.019988
120.3946093.37150.000599
13-0.196349-1.67760.048851
14-0.210748-1.80060.037946
15-0.066905-0.57160.284663
160.0091450.07810.468969
17-0.115706-0.98860.163065
180.1478731.26340.105228
190.1270541.08560.140625
20-0.097304-0.83140.20424
21-0.094635-0.80860.210697
220.0072970.06230.475229
230.024280.20750.418117
24-0.085514-0.73060.233672
250.0854190.72980.233918
26-0.067834-0.57960.281993
27-0.078779-0.67310.251509
280.0399920.34170.366781
29-0.100707-0.86040.196182
30-0.004622-0.03950.484305
31-0.030444-0.26010.397755
320.004440.03790.48492
33-0.001603-0.01370.494556
340.0034210.02920.48838
35-0.10958-0.93630.176115
360.0030030.02570.4898


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')